Neighboring Brain Areas Research Articles

MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model

Background and ObjectiveSleep staging is an essential step for sleep disorder diagnosis, which is time-intensive and laborious for experts to perform this work manually. Automatic sleep stage classification methods not only alleviate experts from these demanding tasks but also enhance the accuracy and efficiency of the classification process. MethodsA novel multi-channel biosignal-based model constructed by the combination of a 3D convolutional operation and a graph convolutional operation is proposed for the automated sleep stages using various physiological signals. Both the 3D convolution and graph convolution can aggregate information from neighboring brain areas, which helps to learn intrinsic connections from the biosignals. Electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG) and electrocardiogram (ECG) signals are employed to extract time domain and frequency domain features. Subsequently, these signals are input to the 3D convolutional and graph convolutional branches, respectively. The 3D convolution branch can explore the correlations between multi-channel signals and multi-band waves in each channel in the time series, while the graph convolution branch can explore the connections between each channel and each frequency band. In this work, we have developed the proposed multi-channel convolution combined sleep stage classification model (MixSleepNet) using ISRUC datasets (Subgroup 3 and 50 random samples from Subgroup 1). ResultsBased on the first expert's label, our generated MixSleepNet yielded an accuracy, F1-score and Cohen kappa scores of 0.830, 0.821 and 0.782, respectively for ISRUC-S3. It obtained accuracy, F1-score and Cohen kappa scores of 0.812, 0.786, and 0.756, respectively for the ISRUC-S1 dataset. In accordance with the evaluations conducted by the second expert, the comprehensive accuracies, F1-scores, and Cohen kappa coefficients for the ISRUC-S3 and ISRUC-S1 datasets are determined to be 0.837, 0.820, 0.789, and 0.829, 0.791, 0.775, respectively. ConclusionThe results of the performance metrics by the proposed method are much better than those from all the compared models. Additional experiments were carried out on the ISRUC-S3 sub-dataset to evaluate the contributions of each module towards the classification performance.

P38 initiates degeneration of midbrain GABAergic and glutamatergic neurons in diabetes models.

Diabetes mellitus may cause tau protein hyperphosphorylation and neurodegeneration, but the exact mechanism by which diabetic conditions induce tau pathology remains unclear. Tau protein hyperphosphorylation is considered a major pathological hallmark of neurodegeneration and can be triggered by diabetes. Various tau-directed kinases, including P38, can be activated upon diabetic stress and induce tau hyperphosphorylation. Despite extensive research efforts, the exact tau specie(s) and kinases driving neurodegeneration in diabetes mellitus have not been clearly elucidated. We herein employed different techniques to determine the exact molecular mechanism of tau pathology triggered by diabetes in in vivo and in vitro models. We showed that diabetes-related stresses and glucose metabolism deficiency could induce cis P-tau (an early driver of the tau pathology) accumulation in the midbrain and corpus callosum of the diabetic mice models and cells treated with 2-deoxy-D-glucose, respectively. We found that the active phosphorylated level of P38 was increased in the treated cells and diabetic mice models. We observed that oxidative stress activated P38, which directly and indirectly drove tau pathology in the GABAergic and glutamatergic neurons of the midbrain of the diabetic mice after 96 h, which accumulated in the other neighboring brain areas after 2 months. Notably, P38 inhibition suppressed tau pathogenicity and risk-taking behaviors in the animal models after 96 h. The data establish P38 as a central mediator of diabetes mellitus-induced tau pathology. Our findings provide mechanistic insight into the consequences of this metabolic disorder on the nervous system.

Early IGF-1 Gene Therapy Prevented Oxidative Stress and Cognitive Deficits Induced by Traumatic Brain Injury.

Traumatic Brain Injury (TBI) remains a leading cause of morbidity and mortality in adults under 40 years old. Once primary injury occurs after TBI, neuroinflammation and oxidative stress (OS) are triggered, contributing to the development of many TBI-induced neurological deficits, and reducing the probability of critical trauma patients´ survival. Regardless the research investment on the development of anti-inflammatory and neuroprotective treatments, most pre-clinical studies have failed to report significant effects, probably because of the limited blood brain barrier permeability of no-steroidal or steroidal anti-inflammatory drugs. Lately, neurotrophic factors, such as the insulin-like growth factor 1 (IGF-1), are considered attractive therapeutic alternatives for diverse neurological pathologies, as they are neuromodulators linked to neuroprotection and anti-inflammatory effects. Considering this background, the aim of the present investigation is to test early IGF-1 gene therapy in both OS markers and cognitive deficits induced by TBI. Male Wistar rats were injected via Cisterna Magna with recombinant adenoviral vectors containing the IGF-1 gene cDNA 15 min post-TBI. Animals were sacrificed after 60 min, 24 h or 7 days to study the advanced oxidation protein products (AOPP) and malondialdehyde (MDA) levels, to recognize the protein oxidation damage and lipid peroxidation respectively, in the TBI neighboring brain areas. Cognitive deficits were assessed by evaluating working memory 7 days after TBI. The results reported significant increases of AOPP and MDA levels at 60 min, 24 h, and 7 days after TBI in the prefrontal cortex, motor cortex and hippocampus. In addition, at day 7, TBI also reduced working memory performance. Interestingly, AOPP, and MDA levels in the studied brain areas were significantly reduced after IGF-1 gene therapy that in turn prevented cognitive deficits, restoring TBI-animals working memory performance to similar values regarding control. In conclusion, early IGF-1 gene therapy could be considered a novel therapeutic approach to targeting neuroinflammation as well as to preventing some behavioral deficits related to TBI.

Toward a Unified Framework for Cognitive Maps.

In this study, we integrated neural encoding and decoding into a unified framework for spatial information processing in the brain. Specifically, the neural representations of self-location in the hippocampus (HPC) and entorhinal cortex (EC) play crucial roles in spatial navigation. Intriguingly, these neural representations in these neighboring brain areas show stark differences. Whereas the place cells in the HPC fire as a unimodal function of spatial location, the grid cells in the EC show periodic tuning curves with different periods for different subpopulations (called modules). By combining an encoding model for this modular neural representation and a realistic decoding model based on belief propagation, we investigated the manner in which self-location is encoded by neurons in the EC and then decoded by downstream neurons in the HPC. Through the results of numerical simulations, we first show the positive synergy effects of the modular structure in the EC. The modular structure introduces more coupling between heterogeneous modules with different periodicities, which provides increased error-correcting capabilities. This is also demonstrated through a comparison of the beliefs produced for decoding two- and four-module codes. Whereas the former resulted in a complete decoding failure, the latter correctly recovered the self-location even from the same inputs. Further analysis of belief propagation during decoding revealed complex dynamics in information updates due to interactions among multiple modules having diverse scales. Therefore, the proposed unified framework allows one to investigate the overall flow of spatial information, closing the loop of encoding and decoding self-location in the brain.

Sub-millimeter fMRI reveals multiple topographical digit representations that form action maps in human motor cortex

The human brain coordinates a wide variety of motor activities. On a large scale, the cortical motor system is topographically organized such that neighboring body parts are represented by neighboring brain areas. This homunculus-like somatotopic organization along the central sulcus has been observed using neuroimaging for large body parts such as the face, hands and feet. However, on a finer scale, invasive electrical stimulation studies show deviations from this somatotopic organization that suggest an organizing principle based on motor actions rather than body part moved. It has not been clear how the action-map organization principle of the motor cortex in the mesoscopic (sub-millimeter) regime integrates into a body map organization principle on a macroscopic scale (cm). Here we developed and applied advanced mesoscopic (sub-millimeter) fMRI and analysis methodology to non-invasively investigate the functional organization topography across columnar and laminar structures in humans. Compared to previous methods, in this study, we could capture locally specific blood volume changes across entire brain regions along the cortical curvature. We find that individual fingers have multiple mirrored representations in the primary motor cortex depending on the movements they are involved in. We find that individual digits have cortical representations up to 3 ​mm apart from each other arranged in a column-like fashion. These representations are differentially engaged depending on whether the digits’ muscles are used for different motor actions such as flexion movements, like grasping a ball or retraction movements like releasing a ball. This research provides a starting point for non-invasive investigation of mesoscale topography across layers and columns of the human cortex and bridges the gap between invasive electrophysiological investigations and large coverage non-invasive neuroimaging.

SA74. Visual Cortex Gamma-Band Power is Reduced in Individuals at Ultra-High Risk for Schizophrenia: An MEG Study

Abstract Background: Emerging evidence suggests that schizophrenia (ScZ) is associated with aberrant neural oscillatory activity, in particular at γ-band frequencies (>30 Hz). Our group has reported several studies showing impaired generation of high-gamma band oscillatory activity (~50–120 Hz) in chronic ScZ patients as well as in unmedicated patients with first-episode psychosis (FEP). Currently, however, it is unclear whether gamma-band activity is already impaired in individuals at Ultra High Risk (UHR) for schizophrenia. The current MEG study investigates this question, using a visual task that is known to induce strong high-γ band activity over visual cortical areas. Methods: MEG data were recorded, while 50 UHR and 30 healthy control (CON) participants performed an inward moving grating task. Participants fixated on sine-wave circular gratings and detected (by button-press) acceleration of inward movement, occurring at an unpredictable moment during trial presentation. MEG analysis focused on frequency domain reconstructed MEG data collected from central nodes placed in 80 (sub)cortical regions defined within the AAL-atlas, using LCMV beamformer source-analysis algorithms to optimally suppress both sensor-level noise sources and contributions from neighboring brain areas. Results: Independent of group (i.e., across all participants), 14 AAL-atlas-derived regions in the visual cortex showed significantly increased sustained gamma-band (53–63 Hz) and significantly decreased sustained alpha-band (8–12 Hz) activity during stimulus presentation, compared to baseline activity (False-Discovery-Rate corrected for multiple comparisons). Subsequently tested group effects (UHRs vs. CONs) across these 14 visual regions and across a time interval between 200 and 1200 ms postgrating onset revealed significantly decreased gamma-band responses for UHR, but no group differences in alpha-band responses. In addition, UHR participants’ performance was characterized by elevated error rates, compared to CON participants. Conclusion: Gamma-band visual-cortex responses during perception are already impaired in individuals at UHR for psychosis development and therefore represent a potential candidate biomarker for psychosis prediction.

M73. Neuromagnetic 40 Hz Auditory Steady State Responses and Auditory Cortical GABA-Levels in Participants at Ultra-High Risk of Psychosis

Abstract Background: The 40 Hz auditory steady state response (ASSR) is robustly impaired in chronic schizophrenia which could reflect impaired GABAergic neurotransmission in auditory cortex. However, little is known about the presence of alterations in the 40 Hz ASSR in early and at-risk stages of psychosis. In the current study, we aimed to explore the 40 Hz ASSR impairments in individuals at ultra-high risk (UHR) of psychosis and the possible relationship of deficits in gamma-band entrainment to dysfunctional GABAergic neurotransmission through measurements of cortical GABA-levels. Methods: Fifty UHR participants recruited from the general public, NHS primary care and mental health services and 25 healthy controls were included as part of the MRC-funded Youth Mental Health Risk and Resilience (YouR)-study. MEG data were recorded while participants were passively presented with a series of 1000 Hz carrier tones amplitude modulated at 40 Hz. These data were analyzed at source-level by reconstruction in the frequency-domain using 98 nodes defined from the AAL-atlas and LCMV beamformer source-analysis algorithms. This approach was employed in order to estimate ASSR responses directly from their generating sources while suppressing sensor-level noise and activity in neighboring brain areas. Finally, GABA/Cr ratios were measured, using 1H-MRS at 3T and 2 × 2 × 2 cm voxels placed in the right visual and bilateral auditory cortices. Results: Across groups, the ASSR stimulus significantly activated 15 AAL nodes (FDR corrected), including auditory areas such as right superior temporal gyrus, right heschl’s gyrus, right medial temporal gyrus and left supramarginal gyrus. Subsequent group comparisons revealed impaired 40 Hz ASSR spectral power in secondary auditory areas in UHR participants, which was maximal at 250–750 ms post-stimulus onset in the left supramarginal gyrus. Furthermore, a significant difference was found for GABA/Cr levels in the right auditory cortex (UHR > controls). Conclusion: These results indicate that the 40 Hz ASSR is impaired in UHR participants, which could be related to aberrant GABAergic neurotransmission in auditory cortex. Accordingly, the 40 Hz ASSR could potentially constitute a biomarker for early detection and diagnosis reflecting changes in the balance between excitation and inhibition in auditory areas.

Tonic Inhibitory Control of Dentate Gyrus Granule Cells by α5-Containing GABAA Receptors Reduces Memory Interference.

Interference between similar memories poses a significant limitation on the hippocampal declarative memory system, and impaired interference management is a cognitive symptom in many disorders. Thus, understanding mechanisms of successful interference management or processes that can lead to interference-related memory problems has high theoretical and translational importance. This study provides empirical evidence that tonic inhibition in the dentate gyrus (DG), which maintains sparseness of neuronal activation in the DG, is essential for management of interference. The specificity of findings to tonic, but not faster, more transient types of neuronal inhibition and to the DG, but not the neighboring brain areas, is presented through control experiments. Thus, the findings link interference management to a specific mechanism, proposed previously by computational models.

Synchronous and Asynchronous Theta and Gamma Activity during Episodic Memory Formation

To test the hypothesis that neural oscillations synchronize to mediate memory encoding, we analyzed electrocorticographic recordings taken as 68 human neurosurgical patients studied and subsequently recalled lists of common words. To the extent that changes in spectral power reflect synchronous oscillations, we would expect those power changes to be accompanied by increases in phase synchrony between the region of interest and neighboring brain areas. Contrary to the hypothesized role of synchronous gamma oscillations in memory formation, we found that many key regions that showed power increases during successful memory encoding also exhibited decreases in global synchrony. Similarly, cortical theta activity that decreases during memory encoding exhibits both increased and decreased global synchrony depending on region and stage of encoding. We suggest that network synchrony analyses, as used here, can help to distinguish between two major types of spectral modulations: (1) those that reflect synchronous engagement of regional neurons with neighboring brain areas, and (2) those that reflect either asynchronous modulations of neural activity or local synchrony accompanied by global disengagement from neighboring regions. We show that these two kinds of spectral modulations have distinct spatiotemporal profiles during memory encoding.

Local/Global Analysis of the Stationary Solutions of Some Neural Field Equations

Neural or cortical fields are continuous assemblies of mesoscopic models, also called neural masses, of neural populations that are fundamental in the modeling of macroscopic parts of the brain. Neural fields are described by nonlinear integro-differential equations. The solutions of these equations represent the state of activity of these populations when submitted to inputs from neighboring brain areas. Understanding the properties of these solutions is essential to advancing our understanding of the brain. In this paper we study the dependency of the stationary solutions of the neural fields equations with respect to the stiffness of the nonlinearity and the contrast of the external inputs. This is done by using degree theory and bifurcation theory in the context of functional, in particular, infinite dimensional, spaces. The joint use of these two theories allows us to make new detailed predictions about the global and local behaviors of the solutions. We also provide a generic finite dimensional approximation of these equations which allows us to study in great detail two models. The first model is a neural mass model of a cortical hypercolumn of orientation sensitive neurons, the ring model [O. Shriki, D. Hansel, and H. Sompolinsky, Neural Comput., 15 (2003), pp. 1809-1841]. The second model is a general neural field model where the spatial connectivity is described by heterogeneous Gaussian-like functions.

The folding fingerprint of visual cortex reveals the timing of human V1 and V2

Primate neocortex contains over 30 visual areas. Recent techniques such as functional magnetic resonance imaging (fMRI) have successfully identified many of these areas in the human brain, but have been of limited value for revealing the temporal dynamics between visual areas. The electroencephalogram (EEG) provides information with high temporal precision, but has had limited success separating out the signals from individual neighboring cortical areas. Consequently, controversies exist over the temporal dynamics across cortical areas. In order to address this problem we developed a new method to identify the sources of the EEG. An individual's unique cortical pattern of sulci and gyri along with a visual area's functional retinotopic layout provides a folding fingerprint that predicts specific scalp topographies for stimuli presented in different parts of the visual field. Using this folding fingerprint with a 96 or 192 location stimulus severely constrains the solution space making it relatively easy to extract the temporal response of multiple visual areas to multiple stimulus locations. The large number of stimuli also provides a means to validate the waveforms by comparing across stimulus sets, an important feature not present in most EEG source identification procedures. Using this method our data reveal that both V1 and V2 waveforms have similar onset latencies, and their temporal dynamics provide new information regarding the response latencies of these areas in humans. Our method enables the previously unattainable separation of EEG responses from neighboring brain areas. While we applied the method to the first two cortical visual areas, V1 and V2, this method is also applicable to somatosensory areas that have defined mappings. This method provides a means to study the rapid information flow in the human brain to reveal top-down and bottom-up cognitive processes.

Signals That Tell Fly Neurons to Extend or Retract

During metamorphosis, fruit fly larvae shed the maggot sheath that had confined their life to a tedious creepy-crawl and don legs, wings, and a pair of big, buggy eyes to explore the third dimension and broaden their horizons. A less conspicuous, but just as wondrous transformation also takes place in their brains. There, new neurons are born and new neural networks are established, which the insects will use to make sense of the environment sampled by their shiny new limbs. How neurons select the appropriate partners among myriad candidates is a long-standing question in neurobiology. And what powers the growth of their axons, the long extensions with which they probe the brain until they reach the right target, is also mostly unknown. Mohammed Srahna, Bassem Hassan, and their colleagues have tackled these issues by genetically manipulating a small cluster of neurons whose axons carve their way through the optic lobe of the fly brain during metamorphosis. The neurons, known as dorsal cluster neurons (DCNs), lie in clusters of approximately 40 near the top of each brain hemisphere. At the end of larval life, they start extending a long axonal branch across the brain, all the way to the opposite optic lobe (contralateral branch). Using a gene construct specifically expressed in the DCN (ato-Gal4-14a), the researchers marked the neurons with a fluorescent protein to follow their axons’ trajectories. A third of the way through metamorphosis, most contralateral branches (30–40) had passed the lobula and reached the medulla, two neighboring brain areas that integrate neuronal inputs coming from the retina. By the adult stage, however, only a dozen contralateral branches remain connected to the medulla. The researchers suspected that the other branches degenerated in the late phases of metamorphosis. Indeed, they observed shortened DCN axons between lobula and medulla in flies mid-way through metamorphosis. But they found no evidence of axon breakdown, such as swelling or fragmentation. They concluded that most DCN axons retracted back to the lobula after reaching the medulla. To probe the mechanics of DCN axon growth and retraction, the researchers blocked specific signaling pathways in the DCN by driving the expression of various gene constructs with ato-Gal4-14a. Blocking the intracellular signaling protein JNK or a receptor (Fz2) for the extracellular signal Wnt prevented the extension of DCN axons beyond the lobula. Blocking another intracellular signaling protein called Rac1 or the receptor for the extracellular signal FGF caused more DCN axons than normal to innervate the medulla. By simultaneously manipulating several pathways, the researchers determined how the pathways interact to regulate DCN axon growth. For instance, blocking JNK suppressed the excessive medulla innervation caused by blocking Rac1. This observation suggests that JNK is necessary for DCN axons to reach the medulla and that Rac1 normally impairs the activity of JNK. Based on additional genetic and biochemical analyses, the researchers propose that JNK signaling is the engine that drives the growth of the DCN axons all the way to the medulla. In the medulla, the axons encounter a localized pool of FGF, which causes some of them to retract back to the lobula. FGF signaling acts by facilitating the inhibition of JNK by Rac1 within the DCN. In contrast, Wnt signaling boosts the activity of JNK by blunting the inhibitory effect of Rac1. The researchers propose that Wnt signaling in DCNs allows axons to maintain their connection to the medulla. Extension or retraction of DCN axons might therefore reflect a different balance of the antagonistic effects of FGF/Rac1 and Wnt/JNK signaling. Single-cell mutations suggest that the integration of these signals is happening in each of the 40 DCNs independently, meaning that the global pattern arises as a result of the autonomous action of individual cells. What remains now to be understood is what makes the 12 or so DCNs that stay connected to the medulla strike that balance differently from their 28 counterparts.

Clinical and anatomical correlates of apraxia of speech

In a previous study ( Dronkers, 1996), stroke patients identified as having apraxia of speech (AOS), an articulatory disorder, were found to have damage to the left superior precentral gyrus of the insula (SPGI). The present study sought (1) to characterize the performance of patients with AOS on a classic motor speech evaluation, and (2) to examine whether severity of AOS was influenced by the extent of the lesion. Videotaped speech evaluations of stroke patients with and without AOS were reviewed by two speech–language pathologists and independently scored. Results indicated that patients with AOS made the most errors on tasks requiring the coordination of complex, but not simple, articulatory movements. Patients scored lowest on the repetition of multisyllabic words and sentences that required immediate shifting between place and manner of articulation and rapid coordination of the lips, tongue, velum, and larynx. Last, all patients with AOS had lesions in the SPGI, whereas patients without apraxia of speech did not. Additional involvement of neighboring brain areas was associated with more severe forms of both AOS as well as language deficits, such as aphasia.

Enlargement of cortical vibrissa representation in the surround of an ischemic cortical lesion.

It has been shown that cortical lesions are associated with an increase of excitability in surrounding brain regions, and with a downregulation of GABA(A) receptors. In the present study we investigated whether this increased excitability affects the cortical map of inputs represented in areas surrounding the lesioned brain area. Focal lesions with a diameter of 2-2.5 mm were induced photochemically in the hindlimb area at the border of the primary somatosensory cortex of the rat. One week after lesioning, the cortical representation of the B3 vibrissa was studied using 14C-deoxyglucose (DG) autoradiography. In all animals mechanical stimulation of the B3 vibrissa produced a column-shaped DG-labeling in the somatosensory cortex, corresponding to the B3-barrel with a maximum of the glucose uptake in layer IV. In control animals without cortical lesions (n=6), stimulation increased the glucose uptake rate by 50.8+/-10.5% in layer IV. In lesioned animals (n=6) maximum DG-uptake in layer IV (54.8+/-8.6%) did not differ significantly from that in controls. However, as compared to control animals, lesioned animals showed also increased glucose uptake within the activated column in layers II/II (51.+/-11.1%, lesioned animals; 31.8+/-11.2%, controls; P<0.05, lesioned vs. control) and V (47.5+/-5.8%, lesioned animals, 28.8+/-10.5%, controls; P<0.05, lesioned vs. control). The diameter of the metabolically activated B3-barrel area of layer IV was expanded from 461.8+/-77.6 microm in control animals to 785.5+/-103.6 microm; P<0.01) in lesioned animals. Lesioned animals also showed expansion of the activated area in layers II/III (890.4+/-134.8 microm, lesioned animals; 430.6+/-95.1 microm, controls; P<0.01) and layer V (1117.5+/-163.6 microm, lesioned animals; 648.7+/-114.1 microm, controls; P<0.01). The depth profile of the activation columns showed a maximum in layer IV in control animals, which was expanded towards layers II/III and layer V in lesioned animals. It is concluded that cortical lesions alter the representational area of neighboring afferent inputs through disinhibition or 'unmasking' of pre-existing silent or ineffectual intracortical synapses. The present observations raise the possibility that the brain supports recovery from lesions by decreasing GABAergic inhibition, thereby facilitating a remapping of the cortical representation in neighboring brain areas.